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Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN

机译：基于智能模糊规则的WSN固定路由检测方法

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In wireless sensor networks (WSNs), energy optimization and the provision of security are the major design challenges. Since the wireless sensor devices are energy constrained, the issue of high energy consumption by the malicious nodes must be addressed well in order to enhance the network performance by making increased network lifetime, reduced energy consumption and delay. In the past, many researchers worked in the provision of new techniques for providing improved security to WSN in order to enhance the reliability in the routing process. However, most of the existing routing techniques are not able to achieve the required security through the use of intelligent techniques for safeguarding the sensor nodes from malicious attacks. In order to address these problems, a new fuzzy temporal clustering-based secured communication model with trust analysis and outlier detection has been developed in this research work. For this purpose, a new fuzzy temporal rule-based cluster-based routing algorithm with trust modelling and outlier detection for monitoring the nodes participating in the communication has been proposed. In addition, a fuzzy temporal rule- and distance-based outlier detection algorithm is also proposed in this paper for distinguishing the malicious nodes from other nodes within each cluster of the network and has been used in the secured routing algorithm. The proposed secure routing algorithm uses the temporal reasoning tasks of explanation-based learning and prediction as well as spatial constraints for making efficient routing decisions through the application of trust and key management techniques for performing effective authentication of nodes and thereby isolating the malicious nodes from communication through outlier detection. By applying these two proposed algorithms for communication in the proposed work, it is proved through experiments that the proposed secure routing algorithm and the outlier detection algorithm are able to perform secured and reliable routing through genuine cluster head nodes more effectively. Moreover, these two algorithms provide improved quality of service with respect to the reliability of communication, packet delivery ratio, reduction in end-to-end delay and reduced energy consumption.
机译：在无线传感器网络（WSN）中，能量优化和提供安全性是主要的设计挑战。由于无线传感器设备是能量约束的，因此必须通过使网络寿命增加，降低能量消耗和延迟来提高网络性能，以便很好地解决恶意节点的高能消耗问题。在过去，许多研究人员在提供了为WSN提供改进的安全性的新技术，以提高路由过程的可靠性。然而，大多数现有路由技术无法通过使用智能技术来实现所需的安全性，以便从恶意攻击中保护传感器节点。为了解决这些问题，已经在本研究工作中开发了一种具有信任分析和远离异常检测的基于新的模糊时间聚类的安全通信模型。为此目的，已经提出了一种新的基于模糊的基于时间规则的基于群集的路由算法，用于监视参与通信的节点的信任建模和异常值检测。另外，本文还提出了一种模糊时间规则和基于距离的异口检测算法，用于区分来自网络的每个集群内的其他节点的恶意节点，并已以安全的路由算法使用。所提出的安全路由算法使用基于解释的学习和预测的时间推理任务以及通过应用信任和密钥管理技术来实现有效的节点的有效认证以及从通信中隔离恶意节点来实现有效路由决策的空间约束通过异常值检测。通过将这两个提议的算法应用于所提出的工作中，通过实验证明了所提出的安全路由算法和异常值检测算法能够更有效地通过真正的群集头节点进行安全和可靠的路由。此外，这两种算法可相对于通信的可靠性，分组传递比，端到端延迟降低和降低能耗而提供了改进的服务质量。

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